The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Design challenges and misconceptions in named entity recognition
Open accessAbstract
We analyze some of the fundamental design challenges and misconceptions that underlie the development of an efficient and robust NER system. In particular, we address issues such as the representation of text chunks, the inference approach needed to combine local NER decisions, the sources of prior knowledge and how to use them within an NER system. In the process of comparing several solutions to these challenges we reach some surprising conclusions, as well as develop an NER system that achieves 90.8 F1 score on the CoNLL-2003 NER shared task, the best reported result for this dataset.
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Cites
A tutorial on hidden Markov models and selected applications in speech recognition
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Lafferty, J., McCallum, A., & Pereira, F. C. N. (2001) · ScholarlyCommons (University of Pennsylvania) · Cited by 12,935
Incorporating non-local information into information extraction systems by Gibbs sampling
Finkel, J. R., Grenager, T., & Manning, C. (2005) · Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics - ACL '05 · doi:10.3115/1219840.1219885 · Cited by 3,008
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Feature-rich part-of-speech tagging with a cyclic dependency network
Toutanova, K., Klein, D., Manning, C. D., & Singer, Y. (2003) · Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - NAACL '03 · doi:10.3115/1073445.1073478 · Cited by 2,844
Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition
Tjong Kim Sang, E. F., & De Meulder, F. (2003) · Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - · doi:10.3115/1119176.1119195 · Cited by 2,788
Predicting good probabilities with supervised learning
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A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition
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Introduction to the CoNLL-2002 Shared Task: Language-Independent Named Entity Recognition
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Cited by
Natural Language Processing (almost) from Scratch
Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., & Kuksa, P. P. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1103.0398 · Cited by 4,962
Neural Architectures for Named Entity Recognition
Lample, G., Ballesteros, M., Subramanian, S., Kawakami, K., & Dyer, C. (2016) · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · doi:10.18653/v1/n16-1030 · Cited by 4,401
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
Ma, X., & Hovy, E. (2016) · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/p16-1101 · Cited by 2,567
Named Entity Recognition with Bidirectional LSTM-CNNs
Chiu, J. P. C., & Nichols, E. (2016) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00104 · Cited by 1,909
(2010) · Cited by 1,906
Metadata
- Authors
- Ratinov, L., & Roth, D.
- Venue
- Proceedings of the Thirteenth Conference on Computational Natural Language Learning - CoNLL '09
- Published
- 2009
- Pages
- 147
- OpenAlex
- W2004763266
- Cited by
- 1,448
- References
- 30
- FWCI
- 31.50
- Type
- conference paper
- Language
- en
- Open access
- gold
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